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Impact of Global and Regional Climate Changes upon the Crop Yields

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The negative impact of global and regional climate changes upon the crop yields leads to the violation of the crop production stability. The development of reliable methods for assessment of the climatic factors by the reaction of the crops to them in order to minimize the impact of climatic stresses upon the sustainability of food systems is an urgent scientific task. This problem was studied on the example of growing corn. A mathematical analysis of the main meteorological indicators for 16 years of research has been performed on the basis of which the frequency and direction of the occurrence of atypical and extreme weather conditions in various periods of the corn vegetation season were established by the coefficient of significance of deviations of the weather elements from the average long-term norm. It has been proved that the probability of occurrence of such weather conditions in the period from April to September is 38–81% in terms of the average temperature of the month, and 31–69% in terms of precipitation. By using the information base of the corn yields in a stationary field experiment with the gradations of factors: A (the fertilizer option) – A1-A12, B (the crop care method) – B1-B3, C (the hybrid) – C1-C7, the most critical month of the corn ontogeny was established when the weather has a decisive influence upon the formation of the crop. With the help of the correlation-regression analysis it was proved that the corn yield most significantly depends on the average monthly temperature in June, and for the hybrids with FАО 200–299 – on the amount of precipitation in the month of May. The obtained mathematical models make it possible to predict the yield of corn at a high level of reliability depending on the indicators of the main climate-forming factors in June, that is, even before the flowering of the plants (before the stage of ВВСН 61).
Słowa kluczowe
Rocznik
Strony
71--77
Opis fizyczny
Bibliogr. 28 poz., tab.
Twórcy
  • National Science Center “Institute of Agriculture” of the National Academy of Agrarian Sciences of Ukraine, 2-b, Mashynobudivnykiv Str., Chabany vil., Kyiv-Sviatoshyn Dist., UA 08162, Kyiv Region, Ukraine
  • National Science Center “Institute of Agriculture” of the National Academy of Agrarian Sciences of Ukraine, 2-b, Mashynobudivnykiv Str., Chabany vil., Kyiv-Sviatoshyn Dist., UA 08162, Kyiv Region, Ukraine
  • National University of Life and Environmental Sciences of Ukraine, 15, Heroyiv Oborony Str., Kyiv, UA 03041 Ukraine
  • National Science Center “Institute of Agriculture” of the National Academy of Agrarian Sciences of Ukraine, 2-b, Mashynobudivnykiv Str., Chabany vil., Kyiv-Sviatoshyn Dist., UA 08162, Kyiv Region, Ukraine
  • Latvia University of Life Sciences and Technologies, 2, Liela str., Jelgava, LV-3001, Latvia
  • Latvia University of Life Sciences and Technologies, 2, Liela str., Jelgava, LV-3001, Latvia
Bibliografia
  • 1. Bachmair S., Tanguy M., Hannaford J., Stahl K. 2018. How well do meteorological indicators represent agricultural and forest drought across Europe? Environmental Research Letters, 13, 034042. https://doi.org/10.1088/1748-9326/aaafda
  • 2. Barwicki J., Gach St., Ivanovs S. 2012. Proper utilization of soil structure for crops today and conservation for future generations. Engineering for Rural Development, 11, 10–15.
  • 3. Baum M., Licht M., Huber I., Archontoulis S. 2020. Impacts of climate change on the optimum planting date of different maize cultivars in the central US Corn Belt. European Journal of Agronomy, 119, 126101. https://doi.org/10.1016/j.eja.2020.126101
  • 4. Bhattarai M., Secchi S., Schoof J. 2017. Projecting corn and soybeans yields under climate change in a Corn Belt watershed. Agricultural Systems, 152, 90–99. https://doi.org/10.1016/j.agsy.2016.12.013
  • 5. Bonea D. 2016. The effect of climatic conditions on the yield and quality of maize in the central part of Oltenia. Annals of the University of Craiova – agriculture, montanology, cadastre series, 46(1), 48–55.
  • 6. Bulgakov V., Gadzalo I., Adamchuk V., Demydenko O., Velichko V., Nowak J., Ivanovs S. 2022. Dynamics of the humus content under different chernozem treatment conditions. Journal of Ecological Engineering, 23(6), 118–128.
  • 7. Chen Y., Marek G., Marek T., Moorhead J., Heflin K., Brauer D., Gowda P., Srinivasan R. 2019. Simulating the impacts of climate change on hydrology and crop production in the Northern High Plains of Texas using an improved SWAT model. Agricultural Water Management, 221, 13–24. https://doi.org/10.1016/j.agwat.2019.04.021
  • 8. Crane-Droesch A. 2018. Machine learning methods for crop yield prediction and climate change impact assessment in agriculture. Environmental Research Letters, 13, 114003.
  • 9. Gaile Z. 2012. Maize (Zea mays L.) response to sowing timing under agro-climatic conditions of Latvia. Žemdirbystė=Agriculture, 99(1), 31–40.
  • 10. Guntukula R., Goyari P. 2020. The impact of climate change on maize yields and its variability in Telangana, India: A panel approach study. Journal of Public Affairs, 20(3), e2088. https://doi.org/10.1002/pa.2088
  • 11. Fatima Z., Ahmed M., Hussain M., Abbas G., Ul-Allah S., Ahmad S., Ahmed N., Ali M., Sarwar G., Haque E., Iqbal P., Hussain S. 2020. The fingerprints of climate warming on cereal crops phenology and adaptation options. Scientific Reports, 10, 18013. https://doi.org/10.1038/s41598-020-74740-3
  • 12. Feng S., Hao Z., Zhang X., Hao F. 2019. Probabilistic evaluation of the impact of compound dry-hot events on global maize yields. Science of the total environment, 689, 1228–1234. https://doi.org/10.1016/j.scitotenv.2019.06.373
  • 13. Hatfield J., Boote K., Kimball B., Ziska L., Izaurralde R., Ort D., Thomson A., Wolfe D. 2011. Climate impacts on agriculture: implications for crop production. Agronomy Journal, 103(2), 351–370. https://doi.org/10.2134/agronj2010.0303
  • 14. Kucharik C., Ramiadantsoa T., Zhang J., Ives A. 2020. Spatiotemporal trends in crop yields, yield variability, and yield gaps across the USA. Crop science, 60(4), 2085-2101. https://doi.org/10.1002/csc2.20089
  • 15. Lobell D., Deines J., Tommaso S. 2020. Changes in the drought sensitivity of US maize yields. Nature Food, 1, 729–735. https://doi.org/10.1038/s43016-020-00165-w
  • 16. Maitah M., Malec K., Maitah K. 2021. Influence of precipitation and temperature on maize production in the Czech Republic from 2002 to 2019. Scientific Reports, 11, 10467. https://doi.org/10.1038/s41598-021-89962-2
  • 17. Moore F., Lobell D. 2014. Adaptation potential of European agriculture in response to climate change. Nature Climate Change, 4, 610–614. https://doi.org/10.1038/nclimate2228
  • 18. Nechyporenko O. 2020. Risk management of global climate change in the agro-industrial complex of Ukraine. The Economy of Agro-Industrial Complex, 4, 6. (in Ukrainian) https://doi.org/10.32317/2221-1055.202004006
  • 19. Parkes B., Sultan B., Ciais P. 2018. The impact of future climate change and potential adaptation methods on Maize yields in West Africa. Climatic Change, 151, 205–217. https://doi.org/10.1007/s10584-018-2290-3
  • 20. Pavlik P., Vlckova V., Machar I. 2019. Changes to land area used for grain maize production in Central Europe due to predicted climate change. International Journal of Agronomy, 9168285, 9. https://doi.org/10.1155/2019/9168285
  • 21. Pinke Z., Lövei G. 2017. Increasing temperature cuts back crop yields in Hungary over the last 90 years. Global Change Biology, 23, 5426–5435. https://doi.org/10.1111/gcb.13808
  • 22. Polevoy A., Kostiukievych T., Tolmachova A., Zhygailo O. 2021. The impact of climatic changes on forming the corn productivity in the western forest-steppe of Ukraine. Ukrainian Black Sea region agrarian science, 1(109), 29-36. (in Ukrainian) https://doi.org/10.31521/2313-092X/2021-1(109)-4
  • 23. Reidsma P., Ewert F., Boogaard H, Diepen K. 2009. Regional crop modelling in Europe: The impact of climatic conditions and farm characteristics on maize yields. Agricultural Systems, 100(1–3), 51–60.
  • 24. Skrypchuk P., Zhukovskyy V., Shpak H., Zhukovska N., Krupko H. 2020. Applied Aspects of Humus Balance Modelling in the Rivne Region of Ukraine. Journal of Ecological Engineering, 21(6), 42–52.
  • 25. Su Y., Gabrielle B., Beillouin D., Makowski D. 2021. High probability of yield gain through conservation agriculture in dry regions for major staple crops. Scientific Reports, 11, 3344. https://doi.org/10.1038/s41598-021-82375-1
  • 26. Welham S.J., Gezan S.A., Clark S.J., Mead A. 2015. Statistical Methods in Biology. Design and Analysis of Experiments and Regression, Chapman and Hall/CRC, 602.
  • 27. Wojciechowski T., Mazur A., Przybylak A., Piechowiak J. 2020. Effect of Unitary Soil Tillage Energy on Soil Aggregate Structure and Erosion Vulnerability. Journal of Ecological Engineering, 21(3), 180–185.
  • 28. Zhang Q., Yang Z. 2019. Impact of extreme heat on corn yield in main summer corn cultivating area of China at present and under future climate change. International Journal of Plant Production, 13, 267–274. https://doi.org/10.1007/s42106-019-00052-w
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1601d173-84c1-45fa-9384-0a79e916d632
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